Single-shot compressed optical-streaking ultra-high-speed photography method and system

ABSTRACT

A system and a method for single-shot compressed optical-streaking ultra-high-speed imaging, the system comprising a spatial encoding module spatially encoding the transient event with a binary pseudo-random pattern into spatially encoded frames; a galvanometer scanner temporally shearing the spatially encoded frames; and a CMOS camera receiving the temporally sheared spatially encoded frames, during one exposure time of the camera, for reconstructing the transient event. The method comprises spatial encoding a transient event; temporal shearing resulting spatially encoded frames of the event, spatio-temporal integration, and reconstruction.

FIELD OF THE INVENTION

The present invention relates to imaging methods. More specifically, thepresent invention is concerned with a single-shot compressedoptical-streaking ultra-high-speed imaging method and system.

BACKGROUND OF THE INVENTION

Single-shot ultra-high-speed imaging methods can be generallycategorized into active-detection and passive-detection methods. Theactive-detection methods use specially designed pulse trains to probe 2Dtransient events, such as (x,y) frames that vary in time, and includefrequency-dividing imaging and time-stretching imaging. Such methods arenot suitable for imaging self-luminescent and color-selective events. Bycontrast, the passive-detection methods use receive-onlyultra-high-speed detectors, such as rotatory-mirror-based cameras,beam-splitting-based framing cameras, in-situ storage image sensor CCD(charge-coupled device) cameras, and global shutter stacked CMOS(complementary metal oxide semiconductor) cameras for example, to recordphotons scattered and emitted from transient scenes. Such cameras eitherhave a bulky and complicated structure or have a limited sequence depth,defined as the number of frames in one acquisition, and pixel count,defined as the number of pixels per frame.

To circumvent these drawbacks, computational imaging methods, combiningphysical data acquisition and numerical image reconstruction, wereincreasingly featured in recent years. In particular, the implementationof compressed sensing (CS) for spatial and/or temporal multiplexing hasallowed overcoming the speed limit with a substantial improvement in thesequence depth and pixel count. Representative methods in computationalimaging methods include programmable pixel compressive camera (P2C2),coded aperture compressive temporal imaging (CACTI), andmultiple-aperture (MA)-CS CMOS camera. However, despite reaching overone megapixel per frame, the imaging speeds of P2C2 and CACTI,inherently limited by the refreshing rate of spatial light modulationand the moving speed of a piezoelectric stage, are limited at severalthousand frames per second (fps), typically to kfps. MA-CS CMOS, despiteultra-high-speed imaging speeds, has a pixel count limited to 64×108with a sequence depth of 32. Thus, existing computational imagingmethods still fail to simultaneously combine high frame rates, sequencedepth, and pixel count for ultra-high-speed imaging.

There is still a need in the art for a ultra-high-speed imaging methodand system.

SUMMARY OF THE INVENTION

More specifically, in accordance with the present invention, there isprovided a system for single-shot compressed optical-streakingultra-high-speed imaging, comprising a spatial encoding module; agalvanometer scanner; and a CMOS camera, wherein the spatial encodingmodule is configured for spatially encoding the transient event with abinary pseudo-random pattern, yielding spatially encoded frames, thegalvanometer scanner temporally shearing the spatially encoded frames ofthe transient event, and the CMOS camera receiving the temporallysheared spatially encoded frames, in one exposure of the camera, forreconstructing the transient event.

There is further provided a method for single-shot compressedoptical-streaking ultra-high-speed imaging, comprising spatial encodinga transient event; temporal shearing resulting spatially encoded framesof the event, spatio-temporal integration, and reconstruction.

Other objects, advantages and features of the present invention willbecome more apparent upon reading of the following non-restrictivedescription of specific embodiments thereof, given by way of exampleonly with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In the appended drawings:

FIG. 1A is a schematic of a system according to an embodiment of anaspect of the present disclosure;

FIG. 1B shows synchronization between the exposure of the CMOS camera(solid line) with an exposure time of t_(e) and the sinusoidal controlsignal of the galvonometer scanner (dashed line) with a period of t_(g)in the system of FIG. 1A;

FIG. 2A is a schematic of a set up for quantifying spatial frequencyresponses of the system of FIG. 1A;

FIG. 2B shows illuminated bars on the resolution target; in the firstpanel, the numbers represent Elements 4 to 6 in Group 2 and Elements 1to 6 in Group 3; the rest of the panels show the projected images ofilluminated bars for different laser pulse widths, calculated by summingthe reconstructed (x,y,t) datacubes along the t axis over voxels;

FIG. 2C shows a comparison of spatial frequency responses of the systemwith different laser pulse widths;

FIG. 3A is a schematic of a set up for assessing multi-scaleultra-high-speed imaging capability of the system of FIG. 1A;

FIG. 3B shows a represented reconstructed frame showing a 300-μs laserpulse passing through a transmissive USAF pattern, at imaging speed of60 kfps; inset showing the time-integrated image captured by the CMOScamera with its intrinsic imaging speed (20 fps);

FIG. 3C shows the normalized intensity of a selected cross section (dashlines in FIG. 3B and FIG. 3E) in the ground truth (circle) and in therepresentative reconstructed frames using 300-μs (solid line) and 10-μs(dashed line) laser pulses;

FIG. 3D shows a comparison of the measured normalized average intensityof the laser pulse as a function of time using the system of FIG. 1A(solid line) and a photodiode (dashed line) for the 300-μs laser pulse;

FIG. 3E shows a represented reconstructed frame showing a 10-μs laserpulse passing through a transmissive USAF pattern, at imaging speed of1.5-Mfp;

FIG. 3F shows a comparison of the measured normalized average intensityof the laser pulse as a function of time using the system of FIG. 1A(solid line) and a photodiode (dashed line) for the 10-μs laser pulse;

FIG. 4A shows an experimental setup for tracing a fast-moving objectusing the system of FIG. 1A;

FIG. 4B shows the time-integrated image of the fast-moving ballpatterns, imaged at the intrinsic frame rate of the CMOS camera (20fps);

FIG. 4C shows the superimposed image of 10 representative time-lapseframes, with an interval of 215 μs, of the same dynamic scene as in FIG.48, imaged by using the system of FIG. 1A;

FIG. 4D shows a comparison of the centroid positions along the x and yaxes between the measurement results and the ground truths; only onedata point being shown for every seven measured data points;

FIG. 5A is a schematical view of a phosphorescence lifetime imagingmicroscopy (PLIM) system according to an embodiment of an aspect of thepresent disclosure;

FIG. 5B shows a representative frame of a movie that presents2-dimensional phosphorescence lifetime decay at 1 microsecond; and

FIG. 5C shows a comparison of the phosphorescence emission decay curvesof four different nanoparticle samples.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The present invention is illustrated in further details by the followingnon-limiting examples.

In a nutshell, a method according to an aspect of the present disclosurecombines compressed sensing with optical streak imaging. The methodcomprises spatially encoding each temporal frame of a scene bycompressed sensing using a spatial encoding module, thereby labeling thecapture time of each frame. Then the method comprises temporal shearingin the temporal domain, using a temporal encoding module, therebycreating an optical streak image, capturing this streak image with anarray detector in a single shot, and obtaining the temporal propertiesof light from this streak image. The mixture of 2D space and time datain the streak image can be processed to separate the data usingreconstruction on the basis of the unique labels attached to eachtemporal frame.

A system 10 according to an embodiment of aspect of the presentdisclosure is illustrated in FIG. 1A.

The system 10 comprises a spatial encoding module 12. The spatialencoding module 12 is a spatial light modulator such as digitalmicromirror device (DMD), AJD-4500, Ajile Light Industries for example,on which a binary pseudo-random pattern is loaded with an encoding pixelsize of 32.4×32.4 μm². Alternatively, the spatial encoding module 12 maybe a printed physical mask with an encoding pattern for example. Thespatial encoding module 12 has a fixed ±12° flipping angle and about 1Mega pixel count.

A transient scene is first imaged into the spatial encoding module 12,where it is spatially encoded by the binary pseudo-random pattern.Resulting spatially encoded frames (c) are then relayed by a 4_(f)system onto a CMOS camera 14 for detection. The CMOS camera 14 may be acell phone, a CCD or a CMOS GS3-U3-23S6M-C, FLIR for example, with aframe rate per second in a range between 1 and 160, for example between15 and 25, and a Mega pixel count.

A galvanometer scanner 16, placed at the Fourier plane of the 4_(f)system, temporally shears (s_(o)) the spatially encoded frames linearlyto different spatial locations along the x axis of the camera 14according to their time of arrival. The galvanometer scanner 16 may be aGS, 6220H, Cambridge Technology, for example. The galvanometer scanner16 is selected with a rotation frequency per second in a range between 1and 160, for example between 15 and 25, and a small angle step response,typically 200 μs.

The image is optically relayed from the transient scene to the CMOScamera 14, by an optical relay module. Four achromatic lens and a mirrorare shown; Lenses 1 and 4 are 75-mm focal length achromatic lenses with1 inch diameter and Lenses 2 and 3 are 100-mm focal length achromaticlenses with 2 inch diameter, such as Thorlabs AC508-100, AC508-075, andthe Mirror may be Thorlabs PF10-03-P01 for example. Alternatively, acamera lens with selected focal length and diameter may be used.

As a result of the spatial encoding of the frames by the binarypseudo-random pattern loaded on the DMD 12, the N frames taken in asingle exposure during the exposure time t of the camera 14 as allowedby rotation of the scanner 16 are ordered. The synchronization betweenthe rotation of the galvanometer scanner 16 and the exposure of thecamera 14 is controlled by a sinusoidal signal (t_(g)) and a rectangularsignal (t_(e)) generated by a function generator (not shown) as shown inFIG. 1B. The function generator may be DG1022z, RIGOL TECHNOLOGIES, INCfor example.

Finally, via spatiotemporal integration (T), the camera 14 compressivelyrecords the spatially encoded and temporally sheared scene as a 2Dstreak image E with a single exposure.

The operation of the system can be described by the following relation:

E=TS _(o) CI(x,y,t),  (1)

where I(x,y,t) is the light intensity of the transient event, crepresents spatial encoding by the DMD 12, s_(o) represents linearlytemporal shearing by the scanner 16 with the subscript “o” standing for“optical”, and T represents spatiotemporal integration by the camera 14.

With prior knowledge or assumptions about the signal, including forexample parameters of the encoding pattern, measured streak image, andphysical forward operators such as spatial encoding, temporal shearing,and integration, and with the spatiotemporal sparsity of the scene, thelight intensity of the transient event I(x,y,t) can be recovered fromthe measurement of the 2D streak image E by solving the inverse problemusing compressed sensing reconstruction as follows:

$\begin{matrix}{\hat{I} = {\underset{I}{argmin}\left\{ {{{E - {{TS}_{o}{CI}}}}_{2}^{2} + {{\lambda\phi}_{TV}(I)}} \right\}}} & (2)\end{matrix}$

where ∥⋅∥₂ ² represents the l₂ norm, λ is a weighting coefficient, andΦ_(TV) is total variation (TV) regularizer. In experiments describedhereinbelow, I(x,y,t) was recovered by using a compressed sensing-basedalgorithm developed upon a two-step iterative shrinkage/thresholdingalgorithm.

To obtain a linearly temporal shearing by the scanner 16, the linearrotation of the galvanometer scanner 16 and the exposure of the camera14 need be synchronized: a static target is placed at the object plane,in the plane of the transient scene in FIG. 1A; and illuminated by apulse laser to generate a transient scene. By tuning the initial phaseof the sinusoidal function (t_(g)), the exposure window of the camera 14is adjusted in search of a peak or valley of the sinusoidal signal(t_(g)), i.e. until local features of the static target are preciselymatched in the streak image due to the symmetric back and forthscanning. Finally, 90° is added to the initial phase of the sinusoidalfunction (t_(g)) to locate the linear slope region of the sinusoidalfunction (t_(g)). The reconstructed movie has a frame rate of:

$\begin{matrix}{{r = \frac{{aUf}_{4}}{t_{g}d}},} & (3)\end{matrix}$

α=0.07 rad/V is a constant that links the voltage added onto thegalvanometer scanner 16, denoted as U, with the deflection angle in itslinear rotation range. f₄=75 mm is the focal length of Lens 4, t_(R) isthe period of the sinusoidal voltage waveform added to the galvanometerscanner 16, and d=5.86 μm is the pixel size of the CMOS camera 14 usedin experiments. In addition, the pre-set exposure time t_(e) of the CMOScamera 14 determines the total length of the recording time window. Ifthe entire streak is located within the CMOS camera 14, the sequencedepth can be calculated by N_(t)=rt_(e). The number of pixels in the Xaxis of each frame, N_(x), can be calculated by N_(x)≤N_(c)+1−N_(t),where N_(c) is the number of pixels in each column of the CMOS camera14. The number of pixels N_(y) in the y axis of each frame is at mostequal to the number of pixels N_(t) in each row of the CMOS camera 14:N_(y)<N_(t).

To characterize the spatial frequency responses of the system 10, singlelaser pulses illuminating through a resolution target 20 were imaged(FIG. 2A). A 532-nm continuous wave laser 22 controlled by an externaltrigger generated laser pulses with different temporal widths. Fivedifferent pulse widths, of 100, 300, 500, 700, and 900 μs, were used toprovide decreased sparsity from 90% to 10% with a step of 20% in thetemporal axis for a recording time window of 1 ms. The system 10 wasused to capture these dynamic scenes at 60 kfps. The first panel in FIG.2B shows illuminated bars corresponding to elements 4 to 6 in Group 2and elements 1 to 6 in Group 3). Movies were reconstructed for eachpulse width and datacubes representing the movies in a format of (x, y,t) were projected onto the x-y plane, as shown in the remaining panelsin FIG. 2B.

These results show that the spatial resolution of the system 10 dependson the sparsity of the transient scene. The contrast as well as theintensity the reconstructed image quality degrades with increasing laserpulse widths. To quantify the performance of the system by consideringboth effects, the normalized product of the contrast and thereconstructed intensity was used as the merit function (FIG. 2C). Forthe 900-μs pulse illumination, Element 3 in Group 3 in thereconstruction has a normalized product below 0.25, which was used asthe threshold to determine the resolvable feature, and the spatialresolution of the system was quantified to be 50 μm.

Thus, a method according to the present disclosure comprise multiplyinga amplitude binary mask for each frame of the event, yielding encodeddatacubes (x,y,t); shifting the different frames to different spatialpositions as a function of their arrival time, yielding spatial-temporalshifting datacubes (x, y+t−1, t); integrating the datacubes as a 2Dimage (x, y+t−1); and retrieving a video from a measurement E of the 2Dimage, with:

E=TS _(o) CI(x,y,t),  (1)

where I(x,y,t) is the light intensity of the transient event, Crepresents spatial encoding, S_(o) represents linearly temporal shearingwith the subscript “o” standing for “optical”, and T representsspatiotemporal integration; and

$\begin{matrix}{\hat{I} = {\underset{I}{argmin}\left\{ {{{E - {{TS}_{o}{CI}}}}_{2}^{2} + {{\lambda\phi}_{TV}(I)}} \right\}}} & (2)\end{matrix}$

where ∥⋅∥₂ ² represents the l₂ norm, λ is a weighting coefficient, andΦ_(TV) is total variation (TV) regularize.

To demonstrate the multi-scale ultra-high-speed imaging capability ofthe system, transmission of single laser pulses was captured through amask. A beam splitter BS was used to divide the incident laser pulseinto two components: the reflected component was recorded by aphotodiode, generating time reference information (ground truth), andthe transmitted component illuminated a transmissive mask with theletters USAF that modulated the spatial profiles of the laser pulses(FIG. 3A), and was then recorded by the system 10.

In a first experiment, a pulse train that contained four 300-μs pulseswas generated. The imaging speed of the system 10 was set to 60 kfps.While the CMOS camera 14, at its intrinsic imaging speed of 20 fps,provided a single image (see SI in FIG. 38) without temporalinformation, the system 10 recorded the spatial profile of the mask andthe intensity time course of the laser pulse in a movie with 240frames/s. A representative frame (t=433 μs) is shown in FIG. 3B.

FIG. 3C shows the normalized intensity of a selected cross section(dashed line in FIG. 3B and FIG. 3E), which demonstrates the wellreconstructed spatial features with respect to the ground truth. Theaverage intensity was also calculated in each frame. The time courseshows a good agreement with the photodiode-recorded result (FIG. 3D).Then the imaging speed was increased to 1.5 Mfps to record a single10-μs laser pulse. The reconstructed movie is Movie 3, and arepresentative frame (t=33 μs) is shown in FIG. 3E. The comparison ofthe time courses of averaged intensity (FIG. 3F) confirmed consistencybetween system and photodiode results under this imaging speed

To demonstrate the ability of the system to track fast moving objects,an animation of a fast-moving ball was imaged (FIG. 4A). The animationcomprised 40 patterns, which were loaded and played by a DMD 30 (such asD4100, Digital Light Innovations) at 20 kHz. A collimated laser beam 32was imaged onto the digital micromirror device 30 at an angle of about240 relative to the surface normal of the DMD 30. The system 10,positioned facing perpendicularly the surface of the DMD 30, collectedthe light diffracted by the patterns at 140 kfps.

FIG. 4B shows a time-integrated image of the dynamic event acquired bythe CMOS camera 14 of the system 10 at its intrinsic frame rate of 20fps.

FIG. 4C shows a color-encoded image generated by superimposing tenrepresentative time-lapse frames, with an interval of 215 μs, of themoving ball from the movies reconstructed by the system 10. While thetime-integrated image merely presents an overall trace, the time-lapseframes show the evolution of the spatial position and the shape of themoving ball, including the deformation of the ball from round toelliptical shape at turning points of its trajectory, at each timepoint.

To evaluate the accuracy of the reconstruction, the centroids of thebouncing ball were traced in each reconstructed frame (FIG. 4D). Themeasurement errors were calculated by subtracting the measured positionof centroids from the pre-set ones. Further, the root-mean-square errors(RMSEs) of reconstructed centroids along the x and y axes werecalculated to be 22 μm and 9 μm, respectively. The anisotropy of theroot-mean-square errors was attributed to the spatiotemporal mixingalong the shearing direction.

The method and system were applied to wide-field phosphorescencelifetime imaging microscopy (PLIM). As illustrated in FIG. 5A, a PLIMsystem 100 according to an embodiment of an aspect of the presentdisclosure comprises an excitation illumination unit 110 and a system 10described hereinabove in relation to FIG. 1A as an imaging unit.

The excitation illumination unit 110 comprises a 980-nm continuouswavelength laser 40, an optical chopper 42, a tube lens 44, an objectivelens 46, a dichroic mirror 48, and an optical band-pass filter 50.

The imaging speed of the imaging system 10 was 1 Mfps. Fourup-conversion nanoparticles (UCNPs) with different core-shell structureswere selected. All samples have a same core structure comprising NaGdF4:Er3+, Yb3+, Sample one having no shell, whereas Sample two to Samplefour each have a shell of additional NaGdF4 around their core, with ashell of increasing thickness from Sample 2 to Sample 4. After pumped by50-μs 980 nm laser pulse from the laser 40, green (center wavelength at545 nm), red (center wavelength at 660 nm) phosphorescence lightemissions, and residual pump 980 nm light were detected by spectroscopy.To explore the green phosphorescence lifetime, the red emission lightand the residual pump light were filtered out using filter 50 withcenter wavelength of 545 nm and spectral bandwidth of ±10 nm.

FIG. 5B shows a representative frame (at t=1 μs) of the movie thatrecords 2-dimensional phosphorescence lifetime decay processing. FIG. 5Cshows the exponential decay curves of the four samples, using pointdetection model where the imaging field of view of the PLIM system wasreduced to a small area, with a diameter of about 100 micrometers. Itcan be seen that Sample one without a shell structure has the shortestlifetime (159 μm), whereas, Samples two to four have an increasedlifetime (from 261 μs to 714 μs), as expected from the structure of thefour UCNPs.

There is thus provided an imaging system comprising a DMD for spatiallyencoding each temporal frame of a scene by compressed sensing, agalvanometer scanner for temporal shearing, thereby creating an opticalstreak image, and a camera for capturing this linear image in a singleshot. The mixture of 2D space and time data in the streak image is thenprocessed to separate the data using reconstruction on the basis of theunique labels attached to each temporal frame by the DMD.

Based on optical streaking using a galvanometer scanner in a 4f imagingconfiguration, the present imaging system, using off-the-shelf camera,provides tunable imaging speeds of up to 1.5 Mfps, which isapproximately three orders of magnitude higher than the state-of-art inimaging speed of compressed sensing-based temporal imaging using siliconsensors, a Megapixel-level spatial resolution, with a pixel count of 0.5megapixels in each frame, and 500-frame sequence depth (i.e. the numberof frames in the movie), and capable of single-shot 2-dimensionalphosphorescence lifetime imaging.

The ultra-high-speed imaging capability of the system was demonstratedby capturing the transmission of single laser pulses through a mask andby tracing the shape and position of a fast-moving object in real time.There is thus provided a single-shot cost-efficiency ultra-high-speeduniversal imaging method and system.

The system may be integrated into a range of imaging instruments frommicroscopes to telescopes, to achieve a scalable spatial resolution bycoupling with different front optics in these imaging instruments.Moreover, the system can be used with different cameras, such as CCD orCMOS cameras according to specific applications, allowing applying themethod to a wide range of wavelengths and for acquiring various opticalcharacteristics such as polarization. For instance, anelectron-multiplying CCD camera may be combined with the system toenable high-sensitivity optical neuroimaging of action potentialpropagating at tens of meters per second under microscopic settings; byleveraging the imaging speed and spatial resolution of the system 10,the method was applied to action potential propagating at tens of metersper second.

As another example, an infrared-camera-based may be integrated to enablewide-field temperature sensing in deep tissue using nanoparticles. Insummary, by leveraging the advantages of off-the-shelf componentsincluding camera, galvo, DMD, and achromatic lenses, the presentinvention provides a system and a method for widespread applications inboth fundamental and applied sciences

Featuring optical streaking using a galvanometer scanner in the 4fimaging system, the all-optical system uses an off-the-shelf CMOS camerawith tunable imaging speeds of up to 1.5 Mfps, which is approximatelythree orders of magnitude higher than the state-of-art in imaging speedof compressed sensing-based temporal imaging using silicon sensors suchas P2C2 and CACTI. In addition, the system can reach a sequence depth ofup to 500 frames and a pixel count of 0.5 megapixels in each frame.

There is thus provided a single-shot compressed optical-streakingultra-high-speed photography system and method, as a passive-detectioncomputational imaging modality with a 2D imaging speed of up to 1.5million frames per second (Mfps), a sequence depth of 500 frame, and an(x,y) pixel count of 1000×500 per frame, using standard imaging sensorstypically limited to 100 frames per second.

The scope of the claims should not be limited by the embodiments setforth in the examples, but should be given the broadest interpretationconsistent with the description as a whole.

1. A system for single-shot compressed optical-streakingultra-high-speed imaging, comprising: a spatial encoding module; agalvanometer scanner; and a CMOS camera; wherein said spatial encodingmodule is configured for spatially encoding the transient event with abinary pseudo-random pattern, yielding spatially encoded frames, saidgalvanometer scanner temporally shearing the spatially encoded frames ofthe transient event, and said CMOS camera receiving the temporallysheared spatially encoded frames, in one exposure of the camera, forreconstructing the transient event.
 2. The system of claim 1, comprisinga function generator, said function generator synchronizing rotation ofthe galvanometer scanner and the exposure of the camera.
 3. The systemof claim 1, comprising an optical relay module relaying the image fromthe transient event to the CMOS camera.
 4. The system of claim 1,wherein said spatial encoding module has a fixed ±12° flipping angle andabout 1 Mega pixel count.
 5. The system of claim 1, wherein said spatialencoding module is a spatial light modulator.
 6. The system of claim 1,wherein said spatial encoding module is one of: i) a digital micromirrordevice ad ii) a printed physical mask with an encoding pattern.
 7. Thesystem of claim 1, wherein said galvanometer scanner is placed at theFourier plane of a 4f system of an optical relay module between thetransient event and the CMOS camera.
 8. The system of claim 1, whereinsaid galvanometer scanner temporally shears the spatially encoded frameslinearly to different spatial locations along an axis of the cameraaccording to their time of arrival.
 9. The system of claim 1, whereinsaid galvanometer scanner is selected with a rotation frequency persecond in a range between 1 and 160, and an angle step response of about200 μs.
 10. The system of claim 1, wherein said galvanometer scanner isselected with a rotation frequency per second in a range between 15 and25 and an angle step response of about 200 μs.
 11. The system of claim1, wherein said CMOS camera has a frame rate, synchronizing with thegalvanometer scanner, in a range between 1 and 160 per second, and aMega pixel count.
 12. The system of claim 1, wherein said CMOS camera,synchronizing with the galvanometer scanner, has a frame rate per secondin a range between 15 and 25, and a Mega pixel count.
 13. A method forsingle-shot compressed optical-streaking ultra-high-speed imaging,comprising spatial encoding a transient event; temporal shearingresulting spatially encoded frames of the event, spatio-temporalintegration, and reconstruction.
 14. The method of claim 13, whereinsaid spatial encoding the transient event comprises spatially encodingthe transient event by a binary pseudo-random pattern, yieldingspatially encoded frames; said temporal shearing of the resultingspatially encoded frames of the event comprises temporally shearing thespatially encoded frames of the event by a galvanometer scanner; saidspatio-temporal integrating comprising integrating resultingspatial-temporal sheared encoded frames into a 2D image; and saidreconstruction comprises recovering a movie from the 2D image recordedby a CMOS camera.
 15. The method of claim 13, wherein said spatialencoding the transient event comprises spatially encoding the transientevent by a binary pseudo-random pattern, yielding spatially encodedframes; said temporal shearing of the resulting spatially encoded framesof the event comprises temporally shearing the spatially encoded framesof the event by a galvanometer scanner; said spatio-temporal integratingcomprising integrating resulting spatial-temporal sheared encoded frameinto a 2D image; and said reconstruction comprises recovering a moviefrom the 2D image recorded by a CMOS camera; the method comprisingsynchronizing a linear rotation of the galvanometer scanner and exposureof the camera.
 16. The method of claim 13, comprising selecting aspatial encoding module having a fixed ±12° flipping angle and about 1Mega pixel count; a galvanometer scanner having a rotation frequency persecond in a range between 1 and 160, and an angle step response of about200 μs; and a CMOS camera having a frame rate per second in a rangebetween 1 and 160, and a Mega pixel count.
 17. The method of claim 13,comprising selecting a spatial encoding module having a fixed ±12°flipping angle and about 1 Mega pixel count; a galvanometer scannerhaving a rotation frequency per second in a range between 15 and 25, andan angle step response of about 200 μs; and a CMOS camera having a framerate per second in a range between 15 and 25, and a Mega pixel count.18. The method of claim 13, comprising imaging the transient event intoa spatial encoding module, the spatial encoding module spatiallyencoding the transient event is by a binary pseudo-random pattern; andrelaying resulting spatially encoded frames by a 4f system onto a CMOScamera.
 19. The method of claim 13, wherein said spatial encoding thetransient event comprises multiplying a amplitude binary mask for eachframe of the event, yielding encoded datacubes (x,y, t); said temporalshearing comprises shifting different frames to different spatialpositions as a function of their arrival time, yielding spatial-temporalshifting datacubes (x, y+t−1, t); said integration comprises integratingdatacubes as a 2D image (x, y+t−1); and said reconstruction comprisesretrieving a video from the 2D image.
 20. The method of claim 13,wherein said spatial encoding of a transient event comprises multiplyinga amplitude binary mask for each frame of the event, yielding encodeddatacubes (x,y, t); said temporal shearing comprises shifting differentframes to different spatial positions as a function of their arrivaltime, yielding spatial-temporal shifting datacubes (x, y+t−1, t); saidintegration comprises integrating the datacubes as a 2D image (x,y+t−1); and said reconstruction comprises retrieving a video from ameasurement E of the 2D image, with:E−TS _(n) CI(x,y,t)  (1) where I(x,y,t) is the light intensity of thetransient event, C represents spatial encoding, S_(o) representslinearly temporal shearing with the subscript “o” standing for“optical”, and T represents spatiotemporal integration; and$\begin{matrix}{\hat{I} = {\underset{I}{argmin}\left\{ {{{E - {{TS}_{o}{CI}}}}_{2}^{2} + {{\lambda\phi}_{TV}(I)}} \right\}}} & (2)\end{matrix}$ where ∥⋅∥₂ ² represents the l₂ norm, λ is a weightingcoefficient, and Φ_(TV) is total variation (TV) regularizer.